function debounce(func, wait) {
    var timeout;
  
    return function () {
      var context = this;
      var args = arguments;
      clearTimeout(timeout);
  
      timeout = setTimeout(function () {
        timeout = null;
        func.apply(context, args);
      }, wait);
    };
  }
  
  // Taken from mdbook
  // The strategy is as follows:
  // First, assign a value to each word in the document:
  //  Words that correspond to search terms (stemmer aware): 40
  //  Normal words: 2
  //  First word in a sentence: 8
  // Then use a sliding window with a constant number of words and count the
  // sum of the values of the words within the window. Then use the window that got the
  // maximum sum. If there are multiple maximas, then get the last one.
  // Enclose the terms in <b>.
  function makeTeaser(body, terms) {
    var TERM_WEIGHT = 40;
    var NORMAL_WORD_WEIGHT = 2;
    var FIRST_WORD_WEIGHT = 8;
    var TEASER_MAX_WORDS = 30;
  
    var stemmedTerms = terms.map(function (w) {
      return elasticlunr.stemmer(w.toLowerCase());
    });
    var termFound = false;
    var index = 0;
    var weighted = []; // contains elements of ["word", weight, index_in_document]
  
    // split in sentences, then words
    var sentences = body.toLowerCase().split(". ");
  
    for (var i in sentences) {
      var words = sentences[i].split(" ");
      var value = FIRST_WORD_WEIGHT;
  
      for (var j in words) {
        var word = words[j];
  
        if (word.length > 0) {
          for (var k in stemmedTerms) {
            if (elasticlunr.stemmer(word).startsWith(stemmedTerms[k])) {
              value = TERM_WEIGHT;
              termFound = true;
            }
          }
          weighted.push([word, value, index]);
          value = NORMAL_WORD_WEIGHT;
        }
  
        index += word.length;
        index += 1;  // ' ' or '.' if last word in sentence
      }
  
      index += 1;  // because we split at a two-char boundary '. '
    }
  
    if (weighted.length === 0) {
      return body;
    }
  
    var windowWeights = [];
    var windowSize = Math.min(weighted.length, TEASER_MAX_WORDS);
    // We add a window with all the weights first
    var curSum = 0;
    for (var i = 0; i < windowSize; i++) {
      curSum += weighted[i][1];
    }
    windowWeights.push(curSum);
  
    for (var i = 0; i < weighted.length - windowSize; i++) {
      curSum -= weighted[i][1];
      curSum += weighted[i + windowSize][1];
      windowWeights.push(curSum);
    }
  
    // If we didn't find the term, just pick the first window
    var maxSumIndex = 0;
    if (termFound) {
      var maxFound = 0;
      // backwards
      for (var i = windowWeights.length - 1; i >= 0; i--) {
        if (windowWeights[i] > maxFound) {
          maxFound = windowWeights[i];
          maxSumIndex = i;
        }
      }
    }
  
    var teaser = [];
    var startIndex = weighted[maxSumIndex][2];
    for (var i = maxSumIndex; i < maxSumIndex + windowSize; i++) {
      var word = weighted[i];
      if (startIndex < word[2]) {
        // missing text from index to start of `word`
        teaser.push(body.substring(startIndex, word[2]));
        startIndex = word[2];
      }
  
      // add <em/> around search terms
      if (word[1] === TERM_WEIGHT) {
        teaser.push("<b>");
      }
      startIndex = word[2] + word[0].length;
      teaser.push(body.substring(word[2], startIndex));
  
      if (word[1] === TERM_WEIGHT) {
        teaser.push("</b>");
      }
    }
    teaser.push("…");
    return teaser.join("");
  }
  
  function formatSearchResultItem(item, terms) {
    return '<div class="search-results__item">'
    + `<a href="${item.ref}">${item.doc.title}</a>`
    + `<div>${makeTeaser(item.doc.body, terms)}</div>`
    + '</div>';
  }
  
  function initSearch() {
    var $searchInput = document.getElementById("search");
    var $searchResults = document.querySelector(".search-results");
    var $searchResultsItems = document.querySelector(".search-results__items");
    var MAX_ITEMS = 10;
  
    var options = {
      bool: "AND",
      fields: {
        title: {boost: 2},
        body: {boost: 1},
      }
    };
    var currentTerm = "";
    var index;
    
    var initIndex = async function () {
      if (index === undefined) {
        index = fetch("/search_index.en.json")
          .then(
            async function(response) {
              return await elasticlunr.Index.load(await response.json());
          }
        );
      }
      let res = await index;
      return res;
    }
  
    $searchInput.addEventListener("keyup", debounce(async function() {
      var term = $searchInput.value.trim();
      if (term === currentTerm) {
        return;
      }
      $searchResults.style.display = term === "" ? "none" : "block";
      $searchResultsItems.innerHTML = "";
      currentTerm = term;
      if (term === "") {
        return;
      }
  
      var results = (await initIndex()).search(term, options);
      if (results.length === 0) {
        $searchResults.style.display = "none";
        return;
      }
  
      for (var i = 0; i < Math.min(results.length, MAX_ITEMS); i++) {
        var item = document.createElement("li");
        item.innerHTML = formatSearchResultItem(results[i], term.split(" "));
        $searchResultsItems.appendChild(item);
      }
    }, 150));
  
    window.addEventListener('click', function(e) {
      if ($searchResults.style.display == "block" && !$searchResults.contains(e.target)) {
        $searchResults.style.display = "none";
      }
    });
  }
  
  
  if (document.readyState === "complete" ||
      (document.readyState !== "loading" && !document.documentElement.doScroll)
  ) {
    initSearch();
  } else {
    document.addEventListener("DOMContentLoaded", initSearch);
  }